Searching for just a few words should be enough to get started. If you need to make more complex queries, use the tips below to guide you.
Issue title: Special Section: Applied Machine Learning and Management of Volatility, Uncertainty, Complexity & Ambiguity (V.U.C.A)
Guest editors: Srikanta Patnaik
Article type: Research Article
Authors: Yu, Hongyana | Ji, Shenjiab; * | Yang, Delic
Affiliations: [a] College of Transportation and Communication, Shanghai Maritime University, Pudong, Shanghai, P.R.China | [b] College of Engineering and Computer Science, The Australian National University, Canberra, ACT, Australia | [c] School of Business, Trinity University, San Antonio, TX, United States
Correspondence: [*] Shenjia Ji, College of Engineering and Computer Science, The Australian National University, 108 North Road, 2600 Canberra, ACT, Australia. E-mail: u5869805@anu.edu.au.
Abstract: Fake online reviews are so prevalent that e-commerce platforms attempt to control it from affecting the trustworthiness between buyers and sellers. The issue has also attracted sporadic scholarly endeavor to understand this new field. To address this issue, we propose a new model to examine three interrelated stakeholders of e-Commerce platforms: experienced buyers, future buyers and the online sellers in terms of purchasing behaviors and sales with three objectives. Experienced buyers influence future consumers’ behaviors and increase sales from sellers. Using data collected from the largest online e-commerce platform in China, we test relevant hypotheses. Our findings show that experienced buyers and their positive reviews increase future buyers’ purchasing and promote corporate sales. These findings contribute knowledge to the online feedback mechanism and literature on fake review studies. This study also provides a novel method to help buyers avoid fake online review from a market structure perspective.
Keywords: Online feedback mechanism, fake online reviews, e-commerce, experienced consumer reviews
DOI: 10.3233/JIFS-179933
Journal: Journal of Intelligent & Fuzzy Systems, vol. 39, no. 2, pp. 1601-1610, 2020
IOS Press, Inc.
6751 Tepper Drive
Clifton, VA 20124
USA
Tel: +1 703 830 6300
Fax: +1 703 830 2300
sales@iospress.com
For editorial issues, like the status of your submitted paper or proposals, write to editorial@iospress.nl
IOS Press
Nieuwe Hemweg 6B
1013 BG Amsterdam
The Netherlands
Tel: +31 20 688 3355
Fax: +31 20 687 0091
info@iospress.nl
For editorial issues, permissions, book requests, submissions and proceedings, contact the Amsterdam office info@iospress.nl
Inspirees International (China Office)
Ciyunsi Beili 207(CapitaLand), Bld 1, 7-901
100025, Beijing
China
Free service line: 400 661 8717
Fax: +86 10 8446 7947
china@iospress.cn
For editorial issues, like the status of your submitted paper or proposals, write to editorial@iospress.nl
如果您在出版方面需要帮助或有任何建, 件至: editorial@iospress.nl